• Title/Summary/Keyword: Local Search Method

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Enhanced VLAD

  • Wei, Benchang;Guan, Tao;Luo, Yawei;Duan, Liya;Yu, Junqing
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.10 no.7
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    • pp.3272-3285
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    • 2016
  • Recently, Vector of Locally Aggregated Descriptors (VLAD) has been proposed to index image by compact representations, which encodes powerful local descriptors and makes significant improvement on search performance with less memory compared against the state of art. However, its performance relies heavily on the size of the codebook which is used to generate VLAD representation. It indicates better accuracy needs higher dimensional representation. Thus, more memory overhead is needed. In this paper, we enhance VLAD image representation by using two level hierarchical-codebooks. It can provide more accurate search performance while keeping the VLAD size unchanged. In addition, hierarchical-codebooks are used to construct multiple inverted files for more accurate non-exhaustive search. Experimental results show that our method can make significant improvement on both VLAD image representation and non-exhaustive search.

Parallel Hybrid Genetic Algorithm-Tabu Search for Distribution System Reconfiguration Using PC Cluster System (배전계통 재구성 문제에 PC클러스터 시스템을 이용한 병렬 유전 알고리즘-타부탐색법 구현)

  • Mun K. J.;Kim H. S.;Park J. H.;Lee H. S.;Kang H. T.
    • Proceedings of the KIEE Conference
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    • summer
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    • pp.36-38
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    • 2004
  • This paper presents an application of parallel hybrid Genetic Algorithm-Tabu Search (GA-TS) algorithm to search an optimal solution of a recokiguration in distribution system. In parallel hybrid CA-TS, after CA operations, stings which are not emerged in the past population are selected in the reproduction procedure. After reproduction operation, if there are many strings which are in the past population, we add new random strings into the population, if there's no improvement for the predetermined iteration, local search procedure is executed by TS for the strings with high fitness function value. To show the usefulness of the proposed method, developed algorithm has been tested and compared on a distribution system in the reference paper.

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Parallel Hybrid Genetic Algorithm-Tabu Search for Distribution System Service Restoration Using PC Cluster System (배전계통 고장복구 문제에 PC 클러스터 시스템을 이용한 병렬 유전 알고리즘-타부탐색법 구현)

  • Mun K. J.;Kim H. S.;Park J. H.;Lee H. S.;Kang H. T.
    • Proceedings of the KIEE Conference
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    • summer
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    • pp.446-448
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    • 2004
  • This paper presents an application of parallel hybrid Genetic Algorithm-Tabu Search (GA-TS) algorithm to search an optimal solution of a service restoration in distribution system. In parallel hybrid GA-TS, after GA operations, strings which are not emerged in the past population are selected in the reproduction procedure. After reproduction operation, if there are many strings which are in the past population, we add new random strings into the population. If there's no improvement for the predetermined iteration, local search procedure is executed by f for the strings with high fitness function value. To show the usefulness of the proposed method, developed algorithm has been tested and compared on a practical distribution system in Korea.

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Optimization of Unit Commitment Schedule using Parallel Tabu Search (병렬 타부 탐색을 이용한 발전기 기동정지계획의 최적화)

  • Lee, yong-Hwan;Hwang, Jun-ha;Ryu, Kwang-Ryel;Park, Jun-Ho
    • Journal of KIISE:Software and Applications
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    • v.29 no.9
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    • pp.645-653
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    • 2002
  • The unit commitment problem in a power system involves determining the start-up and shut-down schedules of many dynamos for a day or a week while satisfying the power demands and diverse constraints of the individual units in the system. It is very difficult to derive an economically optimal schedule due to its huge search space when the number of dynamos involved is large. Tabu search is a popular solution method used for various optimization problems because it is equipped with effective means of searching beyond local optima and also it can naturally incorporate and exploit domain knowledge specific to the target problem. When given a large-scaled problem with a number of complicated constraints, however, tabu search cannot easily find a good solution within a reasonable time. This paper shows that a large- scaled optimization problem such as the unit commitment problem can be solved efficiently by using a parallel tabu search. The parallel tabu search not only reduces the search time significantly but also finds a solution of better quality.

New treatment method for pain and reduction of local anesthesia use in deep caries

  • Yun, Jihye;Shim, Youn-Soo;Park, So-Young;An, So-Youn
    • Journal of Dental Anesthesia and Pain Medicine
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    • v.18 no.5
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    • pp.277-285
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    • 2018
  • Chemo-mechanical caries removal methods are known to be more effective compared with conventional methods in pain reduction. $Carie-care^{TM}$, a chemo-mechanical caries removal agent, was introduced in 2010 but a systematic review of its efficacy has not yet been performed. The purpose of this study was to investigate the effectiveness of $Carie-care^{TM}$ on the outcomes of treatment of caries in children and adolescents. The primary outcome was pain while the secondary outcomes included complete caries removal (CCR), time, need for local anesthesia and behavioral response changes. A Comprehensive literature search was performed in PubMed, EMBASE, and the Cochrane Library up to 30 September 2018. The following keywords were used in the search: 'chemo-mechanical caries removal agent', 'dental caries', 'Carie-care', 'chemo-mechanical caries removal', 'chemo-mechanical caries excavation', other related keywords, and their combinations. From 942 studies identified, 16 were analyzed. Finally, 4 studies met the eligibility criteria and 260 teeth in 120 children and adolescents were included in this review. This review showed that $Carie-care^{TM}$ reduces pain during caries treatment but requires a longer time for effective treatment than conventional methods. Local anesthesia was not required in the Chemo-mechanical caries removal (CMCR) group. In addition, dental anxiety decreased compared to the control group, and co-operation was more positive. Therefore, it may be a useful alternative to conventional methods in children and adolescents, but further verification through additional studies is needed.

Meta-heuristic Method for the Single Source Capacitated Facility Location Problem (물류 센터 위치 선정 및 대리점 할당 모형에 대한 휴리스틱 해법)

  • Soak, Sang-Moon;Lee, Sang-Wook
    • The Journal of the Korea Contents Association
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    • v.10 no.9
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    • pp.107-116
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    • 2010
  • The facility location problem is one of the traditional optimization problems. In this paper, we deal with the single source capacitated facility location problem (SSCFLP) and it is known as an NP-hard problem. Thus, it seems to be natural to use a heuristic approach such as evolutionary algorithms for solving the SSCFLP. This paper introduces a new efficient evolutionary algorithm for the SSCFLP. The proposed algorithm is devised by incorporating a general adaptive link adjustment evolutionary algorithm and three heuristic local search methods. Finally we compare the proposed algorithm with the previous algorithms and show the proposed algorithm finds optimum solutions at almost all middle size test instances and very stable solutions at larger size test instances.

Real Time Scheduling for Multiple Yard Cranes in an Automated Container Terminal (자동화 컨테이너 터미널의 복수 장치장 크레인을 위한 실시간 작업 계획 수립)

  • Park, Tae-Jin;Choe, Ri;Ryu, Kwang-Ryel
    • Journal of Navigation and Port Research
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    • v.31 no.10
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    • pp.869-877
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    • 2007
  • This paper proposes a realtime scheduling method using local search algorithm for non-crossable yard cranes in automated container terminal. To take into consideration the dynamic property of yard crane operation and satisfy the real time constraint, the proposed method repeatedly builds crane schedule for the jobs in a fixed length look-ahead horizon whenever a new job is requested In addition, the proposed method enables the co-operation between yard cranes through prior re-handling and re-positioning in order to resolve the workload imbalance problem between the two cranes, which is one of the primary causes that lower the performance of yard cranes. Simulation-based experiments have shown that the proposed method outperforms the heuristic based methods, and the cooperation scheme contributes a lot to the performance improvement.

Optimal Solution of a Large-scale Travelling Salesman Problem applying DNN and k-opt (DNN과 k-opt를 적용한 대규모 외판원 문제의 최적 해법)

  • Lee, Sang-Un
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.15 no.4
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    • pp.249-257
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    • 2015
  • This paper introduces a heuristic algorithm to NP-hard travelling salesman problem. The proposed algorithm, in its bid to determine initial path, applies SW-DNN, DW-DNN, and DC-DNN, which are modified forms of the prevalent Double-sided Nearest Neighbor Search and searches the minimum value. As a part of its optimization process on the initial solution, it employs 2, 2.5, 3-opt of a local search k-opt on candidate delete edges and 4-opt on undeleted ones among them. When tested on TSP-1 of 26 European cities and TSP-2 of 49 U.S. cities, the proposed algorithm has successfully obtained optimal results in both, disproving the prevalent disbelief in the attainability of the optimal solution and making itself available as a general algorithm for the travelling salesman problem.

Fast Algorithm Based on Successive Elimination Algorithm for Multi-Reference Motion Estimation (다중 참조영상 움직임 추정에 적응을 위한 연속 제거 알고리즘 기반 고속화 알고리즘)

  • Kim Young-Moon;Lee Jae-Eun;Lim Chan;Kang Hyun-Soo
    • Journal of Korea Multimedia Society
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    • v.8 no.7
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    • pp.889-897
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    • 2005
  • This paper presents a new fast motion estimation algorithm for multi-reference frames. We first analyze the experimental results of the successive elimination algorithm, which is a fast version of full search algorithm, being applied to Multi-reference frames. Based on the analysis, a new scheme for alleviating its computational burden is introduced. In the proposed method, the motion vector for the immediately previous reference frame is found by applying the successive elimination algorithm, while the motion vector for other reference frames is estimated by extrapolation of the already obtained motion vector. Adaptively restricting the motion search area to the local area centered on the estimated motion vector, the proposed method provides dramatic computational complexity reduction but slight quality degradation. The proposed method is evaluated by experiments for some image sequences.

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Feature Selection via Embedded Learning Based on Tangent Space Alignment for Microarray Data

  • Ye, Xiucai;Sakurai, Tetsuya
    • Journal of Computing Science and Engineering
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    • v.11 no.4
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    • pp.121-129
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    • 2017
  • Feature selection has been widely established as an efficient technique for microarray data analysis. Feature selection aims to search for the most important feature/gene subset of a given dataset according to its relevance to the current target. Unsupervised feature selection is considered to be challenging due to the lack of label information. In this paper, we propose a novel method for unsupervised feature selection, which incorporates embedded learning and $l_{2,1}-norm$ sparse regression into a framework to select genes in microarray data analysis. Local tangent space alignment is applied during embedded learning to preserve the local data structure. The $l_{2,1}-norm$ sparse regression acts as a constraint to aid in learning the gene weights correlatively, by which the proposed method optimizes for selecting the informative genes which better capture the interesting natural classes of samples. We provide an effective algorithm to solve the optimization problem in our method. Finally, to validate the efficacy of the proposed method, we evaluate the proposed method on real microarray gene expression datasets. The experimental results demonstrate that the proposed method obtains quite promising performance.